Evidence map›Paper›PMID 34718998›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

Functional Annotation from Structural Homology.

Brent W Segelke

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.6field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author at 1 institution in 1 country.

Brent W SegelkePhysical and Life Sciences, Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory, Livermore, CA, USA. segelke1@llnl.gov.
Lawrence Livermore National Laboratory · US

Funding

Resource for Biocomputing Visualization and InformaticsP41GM103311 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI FERRIN, THOMAS E · 2012 to 2017
$8.2M
NIGMS NIH HHS P41 GM103311
6 · The paper itself

Abstract

With the nexus of super computing and the biotech revolution, it seems an era of predictive biology through systems biology may be at hand. Modern omics capabilities enable examination of the state of biological system in exquisite detail. The genome, transcriptome, proteome, and metabolome may all be largely knowable, at least for some model systems, providing a basis for modeling and simulation of molecular mechanisms, or pathways, that could capture a biological system's emergent properties. However, there are significant challenges remaining that impede the realization of this vision, perhaps the most significant being the missing functional annotation of genes and gene products. For even the most well-studied organisms as much as a third of called genes for a given genome are not annotated and more than half may be tenuous. Homology inferred from sequence similarity is the basis for much of genome annotation. Homology inferred from structural similarity could be a powerful complement to sequence-based annotation methods. Structural biology or structural informatics can be used to assign molecular function and may have increasing utility with the rapid growth of gene sequence databases and emerging methods for structure determination, like structure prediction based on coevolution. Here we describe tools and provide example cases using structural similarity at the level of quaternary structure, domain content, domain topology, and small 3D motifs to infer homology and posit function. Ultimately annotation by similarity, be it 3D structure homology or more classically primary sequence homology, must be founded by accurate annotation of one ortholog in the group-understanding every function encoded by a genome remains a major challenge to life science.

Indexed as

Computational BiologyDatabases, GeneticMolecular Sequence AnnotationProteomeProteome3D motifGene annotationMolecular evolutionStructural homologyStructural SuperpositionStructure function

Identifiers

PMID34718998
OpenAlexW3208772156

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.